Top Jira Cloud Migration Challenges and How to Address Them

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Introduction

With Atlassian sunsetting Server deployments and encouraging a cloud-first strategy, many organizations running Jira Data Center are actively planning their transition to Jira Cloud.

In the earlier blogs on Atlassian Community, the following topics were explored:

• Jira Cloud: new tool adoption
• 10 best practices for Jira DC to Jira Cloud migration
• Which Jira Cloud migration approach is right for your organization?

While the above articles help evaluate which migration path to choose, this one focuses on the practical challenges that surface during real-world Jira Cloud migration projects. Migrating from Jira DC to Jira Cloud is more than a platform switch; it involves structured data, configuration, and operational transitions.

This article outlines the seven most common challenges and considerations before starting a migration.

Challenge #1: Downtime and business disruption

One of the most critical hurdles is downtime. Traditional migration methods often require freeze windows, during which teams cannot work in Jira. Large datasets increase cutover time, and global teams can rarely pause operations simultaneously.

The impact of downtime is significant. Missed SLAs, delayed releases, and productivity loss are common when migration windows are underestimated.

Teams should consider whether downtime is acceptable, explore phased or incremental migration models, and clarify what “zero downtime” means in practice. In enterprise scenarios, many organizations evaluate enterprise–grade migration solutions, which allow data transfer without pausing ongoing work.

Challenge #2: Template and configuration differences

Jira DC and Jira Cloud may differ in field configurations, workflow schemes, and custom issue types. Migrating data without addressing these differences can lead to broken mappings and incomplete transfers.

Manual rework becomes inevitable when teams discover mismatched templates or unrecognized workflows post-migration. Some migration approaches prioritize metadata and configuration migration, while others focus on structured data transfer. Understanding this distinction before starting reduces downstream issues.

Teams should evaluate whether configurations need to migrate first, or if data transformation is necessary, and how much restructuring is required. Early planning ensures the migrated environment mirrors intended workflows and minimizes post-migration adjustments.

Challenge #3: Preserving history, relationships, and traceability

Maintaining historical data is crucial, particularly for teams with compliance or governance requirements. CSV export/import methods often fail to retain attachments, links, sprint histories, work logs, and issue relationships.

Broken traceability affects reporting accuracy and audit readiness. Missing comments, attachments, or change history can disrupt governance and slow decision-making.

Before migration, teams should determine whether full change history, attachments, or comments are critical. They should assess whether traceability across issues is mandatory for regulatory audits.

For enterprise-scale projects, advanced migration capabilities such as phased cutover, automated validation, and data transformation are necessary. Enterprise data migration platforms are built to handle these requirements while keeping systems aligned and operational during migration.

Challenge #4: Version compatibility and legacy environments

Not all Jira DC environments are equally prepared for Cloud migration. Some tools require Jira 7.6 or later, so older instances may need pre-upgrades. Legacy customizations, apps, and plugins increase complexity, potentially adding extra projects and timelines before migration begins.

The impact can include extended timelines, additional upgrade cycles, and increased risk of errors. Teams should assess the current Jira version, dependencies on legacy apps, and required upgrade paths. Planning ahead prevents unexpected delays and ensures the migration process proceeds smoothly.

Challenge #5: Migrating marketplace apps and add-on data

Enterprise migrations often extend beyond core issue data in Jira Cloud. Marketplace apps frequently store configurations and data outside standard Jira issue tables, and this information may not migrate automatically. Cloud equivalents may differ in functionality, and native migration tools primarily focus on core Jira data rather than app-specific storage.

As a result, organizations may experience functional gaps, loss of historical app data, or unexpected reconfiguration work after cutover. Careful planning requires creating a complete inventory of installed apps, validating cloud compatibility, and defining an app-specific migration approach to preserve critical configurations and operational continuity.

Challenge #6: Masking sensitive PII data when migration to Jira cloud

Enterprise Jira environments often contain personally identifiable information within issue descriptions, comments, attachments, and custom fields. This may include employee records, customer contact details, contractual data, or regulated information collected over years of system usage. Migrating such data to the cloud without assessment can introduce compliance risks under regional data protection laws.

Organizations must identify sensitive PII early in the migration lifecycle and determine whether it should be masked, anonymized, redacted, or excluded entirely. This requires structured data scanning, field-level evaluation, and clear governance policies before execution begins.

In many cases, not all historical PII needs to move to the cloud. Applying masking rules or excluding sensitive datasets reduces risk exposure while maintaining operational continuity. It also ensures that cloud environments align with internal security standards and regulatory requirements.

Challenge #7: Migrating large datasets without performance impact

Years of accumulated issues, attachments, and change history increase migration volume and complexity. When legacy instances retain large amounts of historical data that have never been archived, the dataset becomes significantly heavier to migrate. Without careful planning around historical data and archiving, migration timelines can extend considerably. Legacy environments often retain years of inactive or obsolete projects, while attachments and change logs continue to grow. As a result, organizations frequently attempt full migrations without first reducing or archiving unnecessary historical data, which increases migration scope and complexity.

Large data volumes can significantly affect migration performance. Organizations may experience extended downtime windows, slower migration execution, and a higher risk of partial migrations or failed runs. To reduce this impact, many teams evaluate their historical data before migration and archive inactive or legacy records so that only relevant datasets are moved to the new environment.

Note: Enterprise teams often evaluate structured archiving and selective migration approaches to balance compliance requirements with performance goals. Approaches supported by enterprise–grade migration solutions like OpsHub Migration Manager help organizations archive older data while keeping it accessible for reference, reporting, or compliance when needed.

A quick checklist before starting your Jira DC to Jira Cloud migration

A practical checklist ensures no details are missed:

• Current Jira version and upgrade requirements
• Number of projects to migrate
• Total custom fields and issue types
• Expected downtime and business impact
• Compliance requirements and PII considerations
• Archive old projects retained for legal hold
• Rollback and contingency plans

Addressing these items upfront minimizes risk and accelerates a smooth migration process.

Conclusion: Migration is a technical project, not just data transfer

Jira Cloud migration is more than moving issues; it is a structured technical project requiring planning, validation, and method selection. Proper preparation helps prevent downtime, data loss, and broken workflows.

Review your approach carefully. Understanding the challenges early allows organizations to preserve traceability, maintain compliance, and ensure operational continuity. When done thoughtfully, the migration provides teams with a modern, scalable Jira Cloud environment, while ongoing projects continue without disruption.